DBMS > Apache Druid vs. EventStoreDB vs. H2 vs. SQream DB

System Properties Comparison Apache Druid vs. EventStoreDB vs. H2 vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS
Time Series DBMS

Event Store

Relational DBMS

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

developers.eventstore.com

www.h2database.com/html/main.html

docs.sqream.com

Developer

Apache Software Foundation and contributors

Event Store Limited

Thomas Mueller

SQream Technologies

Initial release

2012

2005

2017

Current release

29.0.1, April 2024

21.2, February 2021

2.2.220, July 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
OS X
Unix

Linux
Windows

All OS with a Java VM

Linux

Data scheme

yes

schema-less columns are supported

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

With clustering: 2 database servers on different computers operate on identical copies of a database

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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More resources

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